Are autonomous vehicles the way forward for efficient transportation and logistical flow?
Artificial intelligence and adaptability – not just automation – need to be essential elements of independent vehicle design and functionality.
You will have encountered every type of driver on the spectrum if you are a frequent Uber user. Some carefully provide a relaxing experience and a leisurely, smooth ride. Others say very little and drive assertively to show their focus on bringing me rapidly to my destination. Depending on my mood, climate, traffic levels, and a host of other interfering variables, there are days that one might enjoy the original driving style, and others when I prefer the latter heavily. And if the form of a driver does not suit my present preferences, it can make a ride uneasy or even agitating.
Flexible on demand.
The ability of a driver to make contextual modifications to the requirements of a passenger is so determinant of the experience of the passenger that it impacts the quality of the journey more than shock absorption, climate control, or other components that we traditionally considered to be essential to the driving experience. So, if autonomous vehicle technicians want a long-lasting implementation of their artificially smart “drivers,” they must provide contextual learning skills.
Engineered safety vs. perceived.
To date, much of the talk about vehicle automation has concentrated on the engineering problems of bringing passengers from point A to point B securely, which we might call Engineered Safety. However, independent riders will need to go beyond just “maintaining it between the lines” and act in ways that create perceived safety — feeling secure in the midst of continually changing internal and personal circumstances.
But how does this make you feel like a typical traveler?
- You can trust the sensory capacities of your vehicle entirely and feel perfectly comfortable.
Your logic will override your physical fear, so, no more resulting in white knuckles clutching the seat.
Precise scheduling and follow ups.
Autonomous vehicles will redefine road safety.
Autonomous logistics can conserve the quality of goods, with precise checks until the time of delivery.
Perceived safety plays an integral part in our experience when driven by an independent or human driver, but this is not the only consideration — our mood in the manner we can guide and influence our expectations.
Even today, we see mood-based options available in luxury vehicles, with many riders providing either a “sport” or “eco” mode based on their present choice. Imagine that you’re running for the job late. To get you to the office on time, you may enjoy your autonomous vehicle positioning itself more assertively in traffic flow and passing slower cars earlier. On the other hand, if on a Sunday afternoon you’re sharing a ride with your family, you might prefer the vehicle to follow the traffic flow.
Logistics and Autonomous vehicles
It would be sensible to expect your preferences to be met in both of these situations, whether you are riding or ridding yourself. Similarly, to provide a pleasant experience for autonomous vehicles, they will need to be extremely adaptable to passenger feedback.
Consider also delivery companies ‘ varied and dynamic requirements. Autonomous vehicles will need the capacity to adjust their driving style depending on the payload they carry. When carrying a load of fabrics, they may want to prioritize velocity over smoothness, but they will have to do the opposite when selling pets, liquor, or dangerous products.
Artificial Intelligence, not automation.
The capacity to engineer an independent chauffeur relies on machine learning capacities because of the overwhelming amount of nuanced situations that may influence perceived safety and contextual comfort. Not only will autonomous vehicles need to learn the baseline comfort levels of their passengers, but the most common variations for each person using the car. They will also need the capacity to adjust depending on the time context on the fly.
Commuters will need the capacity to interact with their vehicles since they would be a human chauffeur to guide them in this teaching, which implies that interacting vocally with an A.I. Siri-style, or choosing from a menu of alternatives. It will also suggest remembering and defaulting settings for particular situations or proposing those configurations when the context reappears. For example, the next time you’re late for the job, your vehicle should go back to the assertive driving style.
Drawing the line
As producers increasingly solve the Engineering Safety problems of vehicle autonomy, it is also essential that they tackle perceived safety and contextual comfort. These will eventually determine which autonomous vehicles will succeed and fail and how long they will take to achieve widespread acceptance.
Engineers must acknowledge an actual reality as we enter this new era of intelligent mobility: we are unlikely to become logical machines based on driverless vehicle constraints. It is, therefore, vital to make driverless vehicles more human.
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